COVID19 in Erie county

COVID19 cases (Erie county) Last updated: (updated 3/23/2020 7PM EST) Data Source
1	Amherst	31	0	0
2	Buffalo	27	0	0
3	Clarence	6	0	0
4	Hamburg	5	0	0
5	West Seneca	4	0	0
6	Tonawanda	4	0	0
7	Lancaster	3	0	0
8	Orchard Park	3	0	0
9	Elma	2	0	0
10	Cheektowaga	2	0	0
11	Alden	2	0	0
12	Grand Island	2	0	0
13	Lackawanna	1	0	0
14	Aurora	1	0	0
15	Evans	1	0	0
16	Holland	1	0	0
17	North Collins	1	0	0
18	Total	96	0	0
Public Advisories

---
title: "COVID19 in Erie county"
author: "Qiang Hu"
output: 
  flexdashboard::flex_dashboard:
    orientation: rows
    social: menu
    source_code: embed
    vertical_layout: scroll
    navbar:
      - { icon: fa-github, href: "https://github.com/hubentu/COVID19Erie"}
---

```{r setup, include=FALSE, eval=FALSE}
library(flexdashboard)
library(COVID19Erie)
counts <- caseCounts()
Counts <- rbind(counts,
                c(town = "Total", colSums(counts[,-1])))
```

Report
=======================================================================

Row {data-width=400}
-----------------------------------------------------------------------

### confirmed {.value-box}

```{r}
valueBox(
  value = sum(counts$confirmed),
  caption = "Total confirmed cases",
  icon = "fas fa-user-md",
  color = "purple"
)
```


### recovered {.value-box}

```{r}
valueBox(
  value = sum(counts$recovered),
  caption = "Total recovered cases",
  icon = "fas fa-ambulance",
  color = "forestgreen"
)
```

### death {.value-box}

```{r}
valueBox(
  value = sum(counts$deaths),
  caption = "Death cases",
  icon = "fas fa-heart-broken",
  color = "red"
)
```


Column {data-height=800}
-----------------------------------------------------------------------
    
### Map
    
```{r}
caseMap(counts, pubExposed, titlePos = NULL)
```
   
Column {data-height=600}
----------------------------------------------------------------------

### Town cases

```{r}
htmlTable(Counts,
          caption = txtMergeLines("COVID19 cases (Erie county)",
                                  paste("Last updated:", attributes(counts)$update.time),
                                  "Data Source"),
          tfoot = "Public Advisories",
          col.rgroup = rep(c("none", "yellow"), c(nrow(Counts)-1, 1)))
```

### Daily cumulative cases
```{r}
countPlot(historyCount)
```